code: def circuit3_TTN(weights, wires):
      SELWeights1 = np.array(
          [
              [
                  [weights[0][0], weights[0][1], weights[0][2]],
                  [weights[0][0], weights[0][1], weights[0][2]],
              ]
          ]
      )
      SELWeights2 = np.array(
          [
              [
                  [weights[1][0], weights[1][1], weights[1][2]],
                  [weights[1][0], weights[1][1], weights[1][2]],
              ]
          ]
      )
      SELWeights3 = np.array(
          [
              [
                  [weights[2][0], weights[2][1], weights[2][2]],
                  [weights[2][0], weights[2][1], weights[2][2]],
              ]
          ]
      )
      qml.StronglyEntanglingLayers(SELWeights1, wires=wires[0:2])
      qml.StronglyEntanglingLayers(SELWeights2, wires=wires[2:4])
      qml.StronglyEntanglingLayers(
          SELWeights3, wires=[wires[1], wires[3]]
      )
  
imports: import pytest
  import numpy
  import pennylane
  from pennylane.templates.tensornetworks.ttn import compute_indices, TTN
label_desc: Use image node_id 7 for calling a global function with example usage: circuit3_TTN(weights, wires) without return types